Detailed Course Information

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DS 4440 - Modern Neural Networks
Presents a hands-on introduction to modern neural network (deep learning) methods and tools. Covers fundamentals of neural networks, including stochastic gradient descent and backpropagation. Introduces standard and new architectures from simple feedforward networks to generative recurrent and state-of-the-art transformer architectures. Emphasizes using these technologies in practice, via modern toolkits. Reviews applications of these models to various types of data, including images and text. 4.000 Credit hours 4.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Data Science Department Course Attributes: NUpath Analyzing/Using Data, Computer&Info Sci Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: Undergraduate level DS 4400 Minimum Grade of D-

DS 4440 - Modern Neural Networks

Presents a hands-on introduction to modern neural network (deep learning) methods and tools. Covers fundamentals of neural networks, including stochastic gradient descent and backpropagation. Introduces standard and new architectures from simple feedforward networks to generative recurrent and state-of-the-art transformer architectures. Emphasizes using these technologies in practice, via modern toolkits. Reviews applications of these models to various types of data, including images and text.
4.000 Credit hours
4.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Data Science Department

Course Attributes:
NUpath Analyzing/Using Data, Computer&Info Sci

Restrictions:
Must be enrolled in one of the following Levels:
Undergraduate

Prerequisites:
Undergraduate level DS 4400 Minimum Grade of D-

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Detailed Course Information

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